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國 立 交 通 大 學
資訊科學與工程研究所
碩 士 論 文
利用 IEEE 802.11p/1609 技術來縮短緊急車輛
到達事故地點的時間
Employing the IEEE 802.11p/1609 Technology to Shorten
the Arrival Times of Emergency Vehicles to Accidents
研 究 生:徐銘昇
指導教授:王協源 教授
中 華 民 國 九 十 八 年 六 月
利用 IEEE 802.11p/1609 技術來縮短緊急車輛到達事故地點的時間
Employing the IEEE 802.11p/1609 Technology to Shorten
the Arrival Times of Emergency Vehicles to Accidents
研 究 生:徐銘昇 Student:Ming-Sheng Hsu
指導教授:王協源 Advisor:Shie-Yuan Wang
國 立 交 通 大 學
資 訊 科 學 與 工 程 研 究 所
碩 士 論 文
A Thesis
Submitted to Institute of Computer Science and Engineering
College of Computer Science
National Chiao Tung University
in partial Fulfillment of the Requirements
for the Degree of
Master
in
Computer Science
June 2009
Hsinchu, Taiwan, Republic of China
中華民國 九十八 年 六 月
i.
利用IEEE 802.11p/1609技術來縮短緊急車輛到達事故地點的時間
Employing the IEEE 802.11p/1609 Technology to Shorten
the Arrival Times of Emergency Vehicles to Accidents
研 究 生:徐銘昇 指導教授:王協源
國立交通大學
資訊科學與工程研究所
摘 要
事故救援對拯救生命和緊急救護是一個重要的論題。事故救援中的一項議題就是
如何縮短緊急車輛 (例如救護車、消防車、警車) 到達事故現場的時間使得救護作業
可以順利的進行。舉例來說,救護車應盡快地到達車禍現場,如此一來傷患才能盡早
地被照顧到。然而,在大都市的區域裡,塞車可能使得緊急車輛難以快速地到達事故
現場。這是因為在道路上的車輛有時會難以讓出道路讓緊急車輛經過。在這個情況下,
由於無法預期的塞車,拯救傷患或消滅火災的寶貴時間將會被浪費掉而造成無法挽回
的悲劇。
為了解決上述的問題,在此篇論文中,我們提出一種基於 IEEE 802.11p/1609 無線
技術的交通控管機制來控制車流狀況和交通號誌來縮短緊急車輛到達事故現場的時間。
在所提出的機制裡,行控中心用來監控道路上的車流情況並提供交通資訊給緊急車輛。
行控中心會動態地改變道路上的交通號誌來幫助緊急車輛能快速地到達事故現場。
我們的模擬結果顯示,在我們所研究的案例中,我們所提出的機制能夠將緊急車
輛到達事故現場的時間大幅地縮短 30%至 50%。
關鍵字:網路模擬器、IEEE 802.11p/1609、緊急車輛。
ii.
Employing the IEEE 802.11p/1609 Technology to Shorten
the Arrival Times of Emergency Vehicles to Accidents
Student:Ming-Sheng Hsu Advisor:Shie-Yuan Wang
Institute of Computer Science and Engineering
National Chiao Tung University
ABSTRACT
Accident rescue is an important topic for life saving and emergent handling. One issue
of accident rescue is how to shorten the times for emergency vehicles (such as ambulances,
fire engines, and police cars) to arrive at accident scenes so that the emergent events can be
properly processed. For example, an ambulance should arrive at a traffic accident scene as
fast as it can so that the wounded can be taken care of as soon as possible. However, in
metropolitan areas traffic jams may make emergency vehicles difficult to arrive at the
accident scenes. This is because cars on the roads may not have enough space to move
themselves to empty a lane for the pass-through of emergency vehicles. In this condition,
the valuable time for rescuing injured people or extinguishing fire will be wasted due to
undesired traffic jams, which may result in unrecoverable tragedies.
To solve this problem, in this thesis we propose a traffic control mechanism based on
the IEEE 802.11p/1609 radio technology to control the traffic condition and traffic lights to
shorten the time required by emergency vehicles to arrive at accident scenes. In the
proposed mechanism, a traffic control center is deployed to monitor the traffic conditions on
the roads and provide the traffic information for emergency vehicles. The traffic control
center can dynamically adjust the traffic lights on the roads to help emergency vehicles
arrive at accident scenes more quickly.
Our simulation results show that the proposed mechanism can significantly reduce
30% to 50% arrival times required by emergency vehicles to arrive at accident scenes in our
evaluated cases.
Keywords: network simulator, IEEE 802.11p/1609, emergency vehicle.
iii.
誌謝辭
首先必頇感謝恩師王協源教授多年來對我的指導與照顧,從大學的專題開始,我
就在王教授的實驗室下做研究,在專業領域上,經過這幾年的扎實訓練,讓我在研究
與實作上均獲得了非常大的成長;而在立身處事方面,老師亦教予我們許多待人處事
的道理。
感謝口試委員陳裕賢教授、鄭振牟教授以及藍崑展教授特地撥冗前來交通大學,
聽取我們的論文報告並加以指導,在他們的建議下,修正不足之處,讓這篇論文得以
更加完善。
感謝周智良與林志哲兩位學長,在平常的討論中讓我的論文架構更加的完善,也
感謝網路與系統實驗室的每一位成員,與你們的相處與互相合作,讓我了解到團隊合
作的方法與溝通技巧,也充實了我的研究所生活。
最後,感謝父母親對我的栽培和哥哥姐姐平時對我的關懷與照顧,有了你們的包
容和支持,我才能順利的完成碩士學位。
iv.
Contents
摘 要 ......................................................................................................................................... i
ABSTRACT ............................................................................................................................... ii
誌謝辭 ....................................................................................................................................... iii
Contents ..................................................................................................................................... iv
List of Figures ............................................................................................................................. v
List of Tables ............................................................................................................................. vi
Chapter 1. Introduction ........................................................................................................ 1
1.1. Motivation .......................................................................................................... 1
1.2. Problem Description ........................................................................................... 2
1.3. Organization ....................................................................................................... 3
Chapter 2. Background ......................................................................................................... 5
2.1. IEEE 802.11p/1609............................................................................................. 5
2.2. A* Algorithm ...................................................................................................... 9
2.3. ESRI Shapefile ................................................................................................. 12
2.4. The NCTUns Network Simulator ..................................................................... 12
2.4.1. Application-based Node Location Update and Traffic Signal Control .... 13
2.4.2. Application-based WAVE Short Message Transmission............................ 16
2.5. Related Work .................................................................................................... 18
Chapter 3. Design and Implementation of the Simulation Environment ........................... 20
3.1. Module-based Node Location Update and Traffic Signal Control ......................... 20
3.2. Module-based WAVE Short Message Transmission .............................................. 23
3.3. Advantages of Module-based Agent Logic Control ............................................... 25
Chapter 4. Design and Implementation of the Proposed Scheme ...................................... 27
4.1. Design of the Proposed Mechanism ....................................................................... 27
4.2. Design of the Scheme ............................................................................................. 31
4.3. Target Scenario ....................................................................................................... 32
Chapter 5. Simulation Results ............................................................................................ 37
Chapter 6. Future Work ...................................................................................................... 45
Chapter 7. Conclusion ........................................................................................................ 46
Reference .................................................................................................................................. 47
v.
List of Figures
Fig. 2.1 WAVE System Protocol Stack .................................................................... 6
Fig. 2.2 Channel Intervals........................................................................................ 7
Fig. 2.3 WSM Transmission .................................................................................... 8
Fig. 2.4 Operation with a Persistent WBSS ............................................................. 9
Fig. 2.5 Architecture of Application-based Agent Logic Control ......................... 13
Fig. 2.6 Architecture of Application-based WSM Simulation .............................. 17
Fig. 3.1 Architecture of Module-based Agent Logic Control................................ 21
Fig. 3.2 Architecture of Module-based WSM Simulation..................................... 24
Fig. 4.1 A Simple Case of Evacuation Message Delivery ..................................... 29
Fig. 4.2 A Simple Case of Dynamic Traffic Lights Control .................................. 30
Fig. 4.3 The Roadmap near Wan-Fang Hospital on UrMap .................................. 33
Fig. 4.4 The Roadmap near Wan-Fang Hospital on NCTUns ............................... 34
Fig. 5.1 The ATRP Results of Each Scheme on Path 1 under Traffic Condition A
and when TLP is 30 seconds ............................................................................ 38
Fig. 5.2 The ATRP Results of Each Scheme on Path 1 under Traffic Condition B
and when TLP is 30 seconds ............................................................................ 39
Fig. 5.3 The ATRP Results of Each Scheme on Path 1 under Traffic Condition C
and when TLP is 30 seconds ............................................................................ 39
Fig. 5.4 The Arrival Time of Each Scheme on Path 1 under Traffic Condition A
and when TLP is 30 seconds ............................................................................ 40
Fig. 5.5 The Arrival Time of Each Scheme on Path 1 under Traffic Condition B
and when TLP is 30 seconds ............................................................................ 40
Fig. 5.6 The Arrival Time of Each Scheme on Path 1 under Traffic Condition C
and when TLP is 30 seconds ............................................................................ 41
Fig. 5.7 The Arrival Time of Each Scheme on Path 2 under Traffic Condition A
and when TLP is 30 seconds ............................................................................ 42
Fig. 5.8 The ATRP Results of Each Scheme on Path 2 under Traffic Condition A
and when TLP is 30 seconds ............................................................................ 42
Fig. 5.9 The Arrival Time of Scheme A on Path 2 under Traffic Condition A
when TLP is Variable ........................................................................................ 43
Fig. 5.10 The Arrival Time of Scheme D on Path 2 under Traffic Condition A
when TLP is Variable ........................................................................................ 44
Fig. 5.11 The ATRP Results of Scheme D on Path 2 using Various TLPs under
Traffic Condition A ........................................................................................... 44
vi.
List of Tables
Table 4.1 Functions Used in Each Scheme............................................................ 32
Table 4.2 Parameter Settings of the Simulated Scenarios ..................................... 35
Table 4.3 Paths from Hospital to Accidents .......................................................... 35
Table 4.4 Average Vehicle Separation Distance .................................................... 36
Table 5.1 Abbreviations ......................................................................................... 37
1.
Chapter 1. Introduction
Recently the advances of telecommunication systems and chip manufactures enable
smart automobiles equipped with a variety of radios. For example, the Global Position
System (GPS) has been widely deployed in vehicles for travel navigation and GPRS/3G
cellular communication has be deployed in the buses of several public transportation system
for tracking their locations. One promising new communication standard for such vehicular
network is the IEEE 802.11p/1609 specification family, which is proposed for wireless
access in vehicular environments based on DSRC (Dedicated Short Rang Communications)
communication protocol. It aims to achieve the communications between vehicles and
vehicles or vehicles and roadside units. The IEEE 802.11p/1609 network can be used to
convey messages for applications for road safety, traffic condition report, traffic control, etc.
1.1. Motivation
There have been many papers that study how to minimize the preparing time of the
medicine for patient. However, rare papers consider the time required by emergency
vehicles for arriving at accident scenes. Reducing the arrival times of emergency vehicles to
accident scenes allows emergency events to be properly processed before they cause more
damage. For example, if an ambulance arrives at a traffic accident scene in a very short time,
injured people can be taken care of before their body conditions get worse. Another
example is that if a fire engine arrives at the fire scene in a very short time, the fire can be
eliminated before it causes more damage.
To achieve this goal, we propose a traffic control mechanism based on the IEEE
802.11p/1609 radios technology. Because the IEEE 802.11p/1609 specification is still under
development, it is difficult to evaluate the performances of our proposed mechanism with
2.
real 802.11p radios in the real world. Thus, in this thesis we use the simulation approach to
evaluate the performances of the proposed mechanism.
1.2. Problem Description
In this thesis, a traffic control mechanism based on IEEE 802.11p/1609 is proposed.
Each intersection is installed with a RSU (Road-Side Unit) and each vehicle is equipped
with an OBU (On-Board Unit). The traffic control center monitors the traffic condition and
controls the traffic light signal.
Note that, although an emergency vehicle can move itself to the nearby lane,
frequently altering its moving lane is dangerous for itself and may cause traffic accidents.
Especially, emergency vehicles such as ambulances, fire engines, and police cars may move
at a high speed to save time to arrive at accident scenes. Therefore, evacuating vehicles for
emergency vehicles on their way to the accident scenes not only saves the rescue time of
injured people but also reduces the occurrences of accidents for emergency vehicles when
they are moving to accident scenes.
The proposed traffic control mechanism uses three significant functions which are (1)
Moving Path Arrangement, (2) Evacuation Message Delivery, and (3) Dynamic Traffic
Lights Control. For moving path arrangement, the traffic control center will generate a
shortest-time path to the accident scene for emergency vehicle to pass through so that the
emergency vehicle will not waste too much time on choosing moving path. For evacuation
message delivery, the traffic control center will send the evacuation message to a relevant
RSU based on receiving the evacuation request sent from an emergency vehicle. The RSU
will broadcast the evacuation message to nearby vehicles so that they can move themselves
to other lanes and empty a lane in advance for facilitating emergency vehicles’ passing
through. For dynamic traffic lights control, the traffic control center can dynamically switch
3.
the traffic lights into green to avoid the obstruction in the intersection so that the emergency
vehicle will not be jammed when it approaches the intersection.
There are three interesting issues we will discuss in this thesis which are listed as
follows.
(1) How will it affect the performance if we use different function combinations for the
proposed traffic control mechanism: As described previously, there are three functions
that can be used in the traffic control mechanism which are (1) moving path
arrangement, (2) evacuation message delivery, and (3) dynamic traffic lights control.
How will it affect the performance if we use different function combinations for our
traffic control mechanism?
(2) How will it affect the performance of the proposed mechanism if we deploy vehicles
on the road map with different vehicle separation distances: The average vehicle
separation distance (i.e., vehicle density) is different during day and night. Therefore, it
is interesting for us to know how it affects the performance if we deploy vehicles on
the road map with different vehicle separation distances.
(3) How will it affect the performance under different traffic lights periods: In the real
world, traffic lights on a main lane may have longer green time than the less important
lane. Due to this reason, we also interest in the effect of the performance when
applying different traffic lights periods for each scenario.
1.3. Organization
The rest of this thesis is organized as follows. A brief overview of IEEE 802.11p/1609,
A* algorithm, related work, and the NCTUns network simulator is described in Chapter 2.
In Chapter 3, the proposed design and implementation of the simulation environment is
introduced. Using the module-based node location update and traffic signal control
4.
mechanism makes the NCTUns network simulator simulate much more nodes on the
roadmap. In Chapter 4, the design and implementation of the proposed traffic control
mechanism is depicted. The results of the proposed traffic control mechanism applying
distinct schemes for each scenario are shown in Chapter 5. In Chapter 6, the future work is
discussed. Finally, in Chapter 7, the conclusion of this thesis is described.
5.
Chapter 2. Background
This chapter mainly describes the concept of IEEE 802.11p/1609. At first the
architecture of WAVE system is introduced. Then the operation of WAVE system is depicted.
Finally, the A* algorithm, ESRI shapefile, NCTUns network simulator, and related work
will be described in the rest of this chapter.
2.1. IEEE 802.11p/1609
IEEE 802.11p draft standard [4] is an amendment of the IEEE 802.11-2007 standard [5].
It adds wireless access in vehicular environments (WAVE) and defines the enhancements to
the 802.11 standard that is required to support Intelligent Transportation Systems (ITS)
applications. These enhancements include data exchange between vehicles with high-speed
movement and between the vehicles and the roadside unit in the licensed ITS band of 5.9 GHz
(5.85-5.925 GHz).
IEEE 802.11p standard is designed to collaborate with the IEEE 1609 trial-use standard
suite. The required components of WAVE system were specified in IEEE 1609.1—Resource
Manager [6], IEEE 1609.2—Security Services [7], IEEE 1609.3— Networking Services [8],
and IEEE 1609.4—Multi-Channel Operations [9]. The architecture of the IEEE 802.11p/1609
network is depicted in Fig. 2.1. The new network architecture supports the TCP/UDP/IPv6
protocol suite and a new WAVE short message protocol (WSMP). The former is used to
cooperate with existing IP-based network applications and the latter is used to disseminate
small-sized packets that carry emergent safety event, location service, or traffic information,
etc.
6.
In the WAVE system, there are two device types which are On-Board Unit (OBU) and
Road-Side Unit (RSU). OBU is a WAVE device that can operate when in motion and supports
the information exchange with RSUs or other OBUs. RSU is a WAVE device that operates
only on the stationary and supports information exchange with OBUs.
Fig. 2.1 WAVE System Protocol Stack
The WAVE system divides the link channel into two classes of radio channel: a control
channel (CCH), and multiple service channels (SCH). As one can see in Fig. 2.2, the CCH
and SCH are presented by black blocks and gray blocks, respectively. Each channel interval
is 50 milliseconds suggested in IEEE 1609.4 draft standard [9]. The CCH is reserved for
system control messages or WAVE short message (WSM). The SCHs are used for
transmitting WSM or general purpose application data packets via a WAVE Basic Service
Set (WBSS). The WAVE devices need to monitor CCH periodically to acquire system
control messages. The operation of the WAVE system is explained below.
7.
Fig. 2.2 Channel Intervals
In the WAVE system, there are two methods, or protocol stacks, to provide
communication services for applications: WSMP and IPv6. WSMP is unique to IEEE 1609
standards and is expected to be used for special purpose. Applications using WSMP can
initiate a WBSS to make a SCH available for their special use, but this may be unnecessary
since WAVE short messages (WSMs) can be exchanged on the CCH without initiating a
WBSS. As one can see in Fig. 2.3, the WSM can be transmitted from OBU to OBU and
OBU to RSU.
8.
Fig. 2.3 WSM Transmission
The general application data packets can be transmitted via a WBSS using IPv6. The
WAVE device that transmits the WAVE service advertisement (WSA) to initiate a WBSS is
called the provider. A WAVE device is called the user if it participates in the WBSS by
accepting the WSA.
As shown in Fig. 2.4, to establish a WBSS, a provider needs to announce a WAVE
service advertisement (WSA) on the CCH during CCH interval. The WSA contains the
operational information of the WBSS such as the ID of this WBSS and the SCH number for
data transmission. A WBSS can be non-persistent or persistent. The provider can initiate a
non-persistent WBSS by announcing the WSA only on one CCH interval. If the provider
wants to initiate a persistent WBSS, it has to announce the WSA on every CCH interval.
9.
Fig. 2.4 Operation with a Persistent WBSS
2.2. A* Algorithm
In this thesis, the traffic control center will generate the shortest-time path for the
emergency vehicle to pass through. In order to generate the shortest-time path, A* algorithm
is adopted in the traffic control center.
The A* algorithm [10] is a best-first, graph search algorithm that can find the path with
the minimum cost from the source to the destination. This algorithm searches nodes from
source to destination. For each node x, it contains 3 values:
f(x): the heuristic function to determine which node has the highest priority to be
searched, where f(x) = g(x) + h(x)
g(x): the actual path-cost function from source to node x
h(x): the admissible heuristic estimate of the distance from node n to destination
The algorithm maintains a priority queue called the ―open set‖ which contains the
nodes to be searched. The node with the smallest f value in the open set will be searched
first. At each iteration of this algorithm, the node with the smallest f value is removed from
10.
the open set, the f and h values of its neighbors will be updated, and these neighbors will be
added into the open set. This algorithm terminates when the destination node with the
smallest f value is removed from the open set or the open set is empty. The pseudo code of
A* algorithm is shown below.
11.
heuristic_distance(x, y): the linear distance between x and y
edge_length(x, y): the actual edge length between x and y in the road map
A* algorithm pseudo code:
Function InitA*(RoadMap)
for all node x in RoadMap do
g_value[x] := infinity
f_value[x] := infinity
frontNode[x] := undefined
end for
Function A*(RoadMap, Source, Destination)
InitA*(RoadMap)
add Source into OpenSet
g_value[Source] := 0
h_value[Source] := heuristic_distance(Source, Destination)
f_value[Source] := g_value[Source] + h_value[Source]
while OpenSet is not empty
x := node in OpenSet with the smallest f_value
if x = Destination
return generateShortestTimePath(frontNode, Destination)
remove x from OpenSet
for each neighbor y of x
trial_g_value := g_value[x] + edge_length (x, y)
h_value[y] := heuristic_distance(y, Destination)
if trial_g_value < g_value[y]
add y into OpenSet
frontNode [y] := x
g_value[y] := trial_g_value
f_value[y] := g_value[y] + h_value[y]
return fail
Function generateShortestTimePath(frontNode, currentNode)
if frontNode[currentNode] is undefined
return
else
generateShortestTimePath(frontNode, frontNode[currentNode])
add currentNode into ShortestTimePath
12.
2.3. ESRI Shapefile
The GUI program of NCTUns can load the ESRI (Economic and Social Research
Institute) shapefile. GUI will transform intersections and streets in the road map to nodes
and edges and then save road map information into road map configuration file for later use.
The ESRI shapefile or normally called the shapefile is a common used geospatial data
format for geographic information systems software. It is developed by ESRI as an open
specification for data interoperability in ESRI and other software products. The "shapefile"
commonly refers to a series of files with ".shp", ".shx", ".dbf" extensions. The actual
shapefile relates specifically to files with the ".shp" extension. However, this file alone is
incomplete for distribution. The other supporting files are also required.
Shapefiles spatially describes geometries such as points, polylines, and polygons. For
instance, these could represent intersections, roads, loops, etc. Each item may also have
attributes to describe items such as the road name or width.
2.4. The NCTUns Network Simulator
NCTUns network simulator [1] is an integrated simulation platform for vehicular
traffic, communication, and network researches. It combines its original network simulation
capabilities with traffic simulation capabilities, such as roadmap construction, vehicle
driving behavior model, etc. The current released version of NCTUns is 5.0 [2]. It aids the
ability to simulate IEEE 802.11p/1609 network protocol for vehicular wireless network,
including the establishment of WBSS and transmission of WSM.
13.
2.4.1. Application-based Node Location Update and Traffic
Signal Control
Fig. 2.5 shows the architecture of application-based agent logic control over the current
released NCTUns 5.0 network simulator [3]. The architecture consists of five major
components, which are (1) GUI, (2) SE, (3) Command Server, (4) Car Agent(s), and (5)
Signal Agent(s). The roles of these components and their functions are described below.
Fig. 2.5 Architecture of Application-based Agent Logic Control
(1) GUI (Graphic User Interface)
The GUI process provides users an environment where they can easily construct
their own road networks. For instance, road segment construction and vehicle
deployment can be easily specified in a few steps of mouse operation. Users can
construct the road map by themselves or by loading the shapefile using GUI.
14.
Moreover, users can also select/replace network protocols and modify the network
parameters in a few operations. After users finish all the settings of the road networks,
the GUI program will generate necessary configuration files for later use.
With the help of the GUI program, users can save much time in constructing a
network topology with many vehicles and roads. The GUI also has the ability to play
back simulation results of vehicle movement and packet transmission. This play back
ability can greatly help users verify the correctness of their design of vehicle driving
behavior and network protocol.
(2) SE (Simulation Engine)
The main function of SE process is simulating MAC (Media Access Control) layer
and PHY (Physical) layer protocols. For example, SE can simulate the MAC layer of
IEEE 802.11p/1609 network protocol, the propagation delay and the power loss at the
physical layer. In vehicular networks, SE stores car and signal information for
servicing the requests issued from car and signal agents. Both car agent and signal
agent are child processes of SE.
(3) Command Server
Command server is implemented inside the SE. Command server is responsible for
accepting and responding to the requests from applications. Applications, such as car
agent and signal agent, can update or retrieve the car/signal information from
car/signal information database through the help of command server. For example, car
agent can send a request to the command server to get locations of its surrounding
vehicles. When command server receives the request, it will access the car/signal
information database to get the requested surrounding vehicles location and then sends
back the data to car agent.
15.
(4) Car Agent
A car agent is a process run on each vehicle node. There are four important
components in the car agent, which are (1) the car agent logic, (2) a road map database,
(3) socket interfaces, and (4) car/signal information APIs. The car agent logic controls
the automatic driving behavior of the vehicle node on which the car agent is run.
When the simulation begins, the car agent will dynamically update the vehicle nodes
location. As described before, the GUI program will generate a road map
configuration file either by user defined or by loading the road map with shapefile
format. Car agent will load the road map configuration file into its road map database.
The road map database not only stores the location/direction of roads but also the
relationship between each street and intersection. For example, we can know which
street connects two specific intersections from the road map database. The socket
interfaces provide TCP/UDP Internet connections for vehicles to exchange their
information on the road. The car/signal information APIs are the functions that the car
agent logic can utilize to access the car and signal information databases located in the
SE. These car/signal information API functions internally use TCP/IP IPC
(Inter-Process Communication) connections between the car agent and the command
server. For instance, car agent can use the car/signal information API function to send
a request to command server. While command server receives this request, it will
access/update the car and signal information database and send back the data that car
agent required.
(5) Signal Agent
A signal agent is a process run up for each traffic light at each intersection. It is
responsible for controlling the signal state of the four traffic lights located at the
intersection. Signal agent has two main components, which are (1) the signal agent
16.
logic and (2) the signal information APIs. The signal agent logic governs when the
signal state should be updated and what color of traffic lights to be changed into. The
signal information APIs are called by the signal agent to update the signal information
database stored in the SE. These signal information API functions internally use
TCP/IP IPC (Inter-Process Communication) connections between the signal agent and
the command server.
During simulation, the statuses of all traffic lights on the roadmap are changed on
the same time and the time period of green and red lights are the same by default.
2.4.2. Application-based WAVE Short Message Transmission
WSM (WAVE Short Message) can be implemented inside the car and signal agent. As
such, car and signal agent can use WSM to transmit small sized information to each other.
Fig. 2.6 shows how network protocol stacks and the transmission of WSM are simulated on
NCTUns. In the example, two vehicles move on the road and they exchange WSM packets
with each other. To simulate this case, two car agents are run up for each vehicle and control
these two vehicles’ moving behaviors. In addition, SE is run up to simulate the WME
(WAVE Management Entity), MAC (Media Access Control) layer, and PHY (Physical)
layer of IEEE 802.11p/1609 protocol stacks. Suppose that the left car agent sends a WSM
packet to the right car agent, the detailed procedure of WSM packet delivery is described
below.
17.
Fig. 2.6 Architecture of Application-based WSM Simulation
1. The car agent logic of the sending car encapsulates its data as a WSM packet and
uses IPC command to send out this WSM data packet to the command server inside
the SE.
2. When command server receives this IPC command from car agent, it will
decapsulate this IPC command to retrieve the WSM packet and then send this
WSM packet to the sending WME to start the procedure of WSM packet
transmission.
3. The WME protocol, MAC protocol, and PHY protocol are simulated in SE. When
this WSM packet arrives at the sending WME, this WSM packet will be
encapsulated with a MAC header and then sent from the sending PHY to the
18.
receiving PHY. The channel model (CM) module is used to simulate the power loss
of the packet on the air.
4. The MAC header of the WSM packet will be stripped off when this packet arrives
at the receiving MAC. When this WSM packet arrives at the receiving WME
module, it will be sent to the command server.
5. The command server will send out this WSM packet using IPC command to the
receiving car agent.
6. Finally, the agent logic of the receiving car agent retrieves the WSM packet from
the IPC command sent from the command server.
2.5. Related Work
In [11], the authors proposed a Fast Emergency Preemption Systems (FAST). The
system can detect the approach of the emergency vehicles to the intersection and change the
traffic light for emergency vehicles. However, the system doesn’t provide the ability to
pre-evacuate vehicles on the shortest-time path for emergency vehicles to pass through.
In [12], the authors used a centralized control mechanism to control the traffic
condition for emergency vehicles to pass by. However, the mechanism doesn’t provide the
control of the traffic lights. Therefore, when the signal is red, there is still a great
opportunity that the emergency vehicle may be blocked in the traffic jam. In the real world,
if the emergency vehicles are close to the traffic lights, they can directly pass the
intersection without concerning the traffic light. However, it is very dangerous and may
cause another traffic accident.
In [13], the authors propose a mechanism that can reduce the traffic chaos by
evacuating vehicles. However, it doesn’t have the ability to control the traffic lights. In [14],
the authors propose a learning real-time routing system for emergency vehicles. This system
19.
can control the traffic light to make the emergency vehicles arrive at the accident fast and
safely. However, it doesn’t have the ability to make surrounding vehicles make the way for
emergency vehicles to pass through. If the emergency vehicles switch lane in high speed
frequently, it is very dangerous and may cause another traffic accident.
20.
Chapter 3. Design and Implementation
of the Simulation Environment
NCTUns network simulator can be used to simulate the vehicular networks. In this
thesis, we want to simulate a large-scale vehicular network and therefore we need to deploy
a lot of cars and traffic lights on the road map. However, as described in Chapter 2.4, the
current released version of NCTUns 5.0 uses application-based agent logic control. Each car
occupies one car agent process and each group of traffic lights at one intersection occupies
one signal agent process. Therefore, SE needs to create a lot of child processes to simulate a
vehicular network with a large amount of vehicles and traffic lights. It will cost a lot of
waiting time for IPC communication and context switch between processes and thus lead to
low performance of the simulation. Therefore, we need to modify the architecture of
NCTUns’s agent logic control mechanism to enhance its simulation performance.
3.1. Module-based Node Location Update and
Traffic Signal Control
Fig. 3.1 shows the architecture of the module-based node location update and traffic
signal logic control platform. The architecture consists of eight elements, which are (1) GUI,
(2) SE, (3) Node Module, (4) Car Agent Logic, (5) Signal Agent Logic, (6) Car Information
Database, (7) Signal Information Database, and (8) Road Map Database. The roles of these
elements and their functions are described below.
21.
Fig. 3.1 Architecture of Module-based Agent Logic Control
(1) GUI (Graphic User Interface)
The GUI program provides users an convenient platform to construct a road
network. Users can decide whether vehicles should be run by the
application-based logic control or module-based logic control with a few
operations. For example, if users want all vehicles are driven by the module-based
logic control, they can deploy the car with the module-based logic control icon on
the road map. By the help of GUI, users can also easily decide whether the traffic
lights on the specified intersections should be controlled by the application or
module. When all the settings are done, GUI will generate configuration files for
later use.
(2) SE (Simulation Engine)
SE is not only responsible for simulating the MAC (Media Access Control)
layer and PHY (Physical) layer protocols but also responsible for updating the
22.
node location and signal status. During the simulation, SE will periodically
transmit the node location and signal status to GUI. As such, GUI program can
use the information to display the simulation status during simulation and play
back simulation results when simulation is done.
(3) Node Module
Node module is implemented in the SE. It also stores the car information
database. Each vehicle node on the GUI is equipped with a node module. An
intersection is represented as a node on the GUI and is also equipped with a node
module, so that the traffic lights on the intersection can be controlled by the signal
agent logic in node module.
(4) Car Agent Logic
Car agent logic is implemented in the node module. A vehicle controlled by
car agent logic has the driving behaviors such as lane switching,
accelerate/decelerate, car following, traffic lights recognition, etc. Car agent logic
will periodically update vehicle’s location by inserting the location update event
into the event scheduler in SE. Each car can directly access the car information
database to get necessary car information. For example, one vehicle can get other
vehicles’ locations by querying the car information database. The car can also
access the signal information database to get the traffic lights information.
(5) Signal Agent Logic
Signal agent logic is also implemented in the node module. The node module
which controls the traffic lights will update its traffic light periodically by
inserting the signal status update event into the event scheduler in SE. Signal
agent logic can directly access the signal information database to update its signal
status.
23.
(6) Car Information Database
Car information database stores the vehicle’s current driving status, such as
its current moving direction, the current road where it is located, its current
moving speed, etc.
(7) Signal Information Database
Signal information database stores the signal’s current traffic light status,
such as the current status of traffic light and the signal’s location.
(8) Road Map Database
Road map database is stored in SE. It provides the road map information to
car agent, such as road’s direction, road number, road’s location, intersection
location, the relationship between each roads and intersections, etc.
3.2. Module-based WAVE Short Message
Transmission
Module-based WSM (WAVE Short Message) is implemented in node module. As such,
the module-based car and signal agent can use WSM to transmit small sized information to
each other. Fig. 3.2 shows how network protocol stacks and the transmission of
module-based WSM are simulated on NCTUns. In the example, two module controlled
vehicles move on the road and they exchange WSM packets with each other. To simulate
this case, two module-based car agents are responsible for each vehicle and control these
two vehicles’ moving behaviors. In addition, SE is run up to simulate the WME (WAVE
Management Entity), MAC (Media Access Control) layer, and PHY (Physical) layer of
IEEE 802.11p/1609 protocol stacks. Suppose that the left module-based car agent sends a
WSM packet to the right module-based car agent, the detailed WSM packet delivery
procedure is described below.
24.
1. The module-based car agent logic of the sending node module encapsulates the
WSM packet and sends this WSM packet to the WME inside the SE.
2. The WME, MAC, and PHY protocols are simulated in SE. When this WSM packet
arrives at the sending WME, this WSM packet will be encapsulated with a MAC
header and then sent from the sending PHY to the receiving PHY. The channel
model (CM) module is used to simulate the power loss of the packet on the air.
3. The MAC header of the WSM packet will be stripped off when this packet arrives at
the receiving MAC. When this WSM packet arrives at the receiving WME module,
it will be sent to the receiving node module.
4. Finally, the module-based car agent logic of receiving node module retrieves the
WSM data from this WSM packet.
Fig. 3.2 Architecture of Module-based WSM Simulation
25.
3.3. Advantages of Module-based Agent Logic
Control
Module-based car agent and signal agent logic control has three main advantages,
which are (1) break the limitation of simulated node numbers, (2) efficient information
update, and (3) reduce required memory space. Those benefits are described below.
(1) Break the Limitation of Simulated Node Numbers
The IP address format on NCTUns is 1.0.subnetID.hostNumberOnThisSubnet,
where subnetID and hostNumberOnThisSubnet are automatically assigned by NCTUns
GUI program. Due to this address format, NCTUns allows a simulation case to have up
to 254 subnets (subnetID 0 and 255 are excluded because they are used for broadcast
purposes), each of which can have up to 254 nodes (hostNumberOnThisSubnet 0 and
255 are excluded because they are also used for broadcast purposes). Therefore, in
total a maximum number of 254 * 254 = 64,516 layer-3 interfaces can be supported in
a simulation case.
Although in theory, NCTUns can deploy up to 64,516 nodes in a simulation case,
in practice it is rarely achieved. This is because each node requires a layer-3 interface
and each layer-3 interface needs to be simulated by a tunnel network interface.
However, currently the installation script creates only 4,096 tunnel interfaces on a
UNIX machine by default. Therefore, the current NCTUns can support a simulation
case using up to 4,096 layer-3 interfaces. This also means that currently the maximum
number of IEEE 802.11p nodes in a vehicular network topology cannot exceed 4,096.
(This is because each IEEE 802.11p node occupies a layer-3 interface.) This limitation
can be easily raised to a number such as 8,192 by creating more tunnel interfaces on
the UNIX machine. However, it is still not enough to simulate a large-scale vehicular
network. We can use module-based agent logic control to simulate the moving
26.
behaviors and WSM transmission of large-scale vehicles. Using the module-based
agent logic control doesn’t occupy any tunnel interface, and therefore we can simulate
up to 64,516 nodes.
(2) Efficient Information Update
The original car and signal agent processes need to use IPC commands to get
information from SE process. Because the IPC command is blocking system call, it
will cost a lot of time to wait for the response from SE. For example, if the car agent
sends a location update command to SE using IPC, it needs to wait till SE returns the
success message of updating location. Also, when car/signal agent process finishes its
job, it will return the CPU control to SE so that SE can continue its jobs such as refresh
the virtual time, simulate network protocol, etc. However, when the number of car and
signal agent processes increases, the context switch time between processes will be
significant. Using module-based car and signal agent logic control instead can save the
time of IPC communication and context switch between processes.
(3) Reduce Required Memory Space
Original car and signal agent are the processes forked by SE process. As one can
see in Fig. 2.5, each car agent process has one copy of the road map database.
Therefore, it will require plenty of memory to store the same roadmap data if there are
a lot of vehicles deployed on the road map. Using module-based car agent logic control,
there is only one copy of road map database in SE and it reduces the memory space
occupied by agent processes.
27.
Chapter 4. Design and Implementation
of the Proposed Scheme
In this chapter, we will describe the design of the proposed traffic control mechanism,
design of the scheme, and target scenarios.
4.1. Design of the Proposed Mechanism
The proposed traffic control mechanism utilizes three functions, which are (1) moving
path arrangement, (2) evacuation message delivery, and (3) dynamic traffic lights control, to
make emergency vehicle drive fast and smoothly. Designs of these three functions are
described below.
(1) Moving Path Arrangement
The traffic control center will arrange a moving path for the emergency vehicle to
reach the accident scene. This moving path must be the shortest-time path to avoid
emergency vehicle driving on the longer-time path to the accident scene. The shortest-time
path generation is based on the A* algorithm. A* algorithm is a best-first, graph search
algorithm that can find the path with the minimum cost from the source to the destination.
The procedure of generating shortest-time path for emergency vehicles is described below.
1. When Wan-Fang hospital receives an emergency call for an accident, it reports the
location of the accident to the traffic control center.
2. When the traffic control center receives the report, it will generate a shortest-time
path from the source (Wan-Fang hospital) to the destination (the reported location
of the accident). The traffic control center then transmits the path back to the
hospital so that the emergency vehicle can drive based on the shortest-time path.
28.
(2) Evacuation Message Delivery
The evacuation message encapsulated in the WSM (WAVE Short Message) is used to
inform the nearby vehicles of the approaching of emergency vehicles so that vehicles can
make their way for emergency vehicles. The procedure of evacuation message delivery is
described below.
1. The emergency vehicle periodically broadcasts the evacuation request message
encapsulated in the WSM to the nearby RSU. The message contains the ID and the
location of the emergency vehicle.
2. While the RSU near the emergency vehicle receives the evacuation request
message, it delivers this message to the traffic control center through the wired
link.
3. When the traffic control center receives the message, because it knows the moving
path of the specified emergency vehicle ID, it sends a new evacuation message to
the RSU which is installed at the intersection in front of the specified emergency
vehicle. This new evacuation message contains the current and next road segment
IDs which the emergency vehicle will pass through.
4. When the RSU which is installed at the intersection in front of the emergency
vehicle receives the new evacuation message, it broadcasts the message using
WSM to inform the nearby vehicles.
5. When the vehicle receives the WSM message, if it may block the way of the
emergency vehicle based on the road segment IDs contained in the message, it will
make the way for the emergency vehicle. So that the emergency vehicle can drive
without been obstructed by other vehicles.
29.
Fig. 4.1 A Simple Case of Evacuation Message Delivery
For example, as one can see in Fig. 4.1, the emergency vehicle (node 7) periodically
broadcasts the evacuation request message using WSM which contains its vehicle ID and
location. The RSU (node 4) installed on the nearest intersection will receive this WSM
message and then deliver this message to the traffic control center (node 5). When the traffic
control center receives the evacuation request, it will find out the current and next road
segment IDs of the specified emergency vehicle based on the shortest-time path. Then, the
traffic control center will sends the evacuation message which contains the current and next
road segment IDs of the emergency vehicle to the RSU (node 3) which is installed in front
of the specified emergency vehicle. The RSU (node 3) will then broadcast the evacuation
message using WSM to nearby vehicles (node 8, 9, 10, and 11). When vehicles (node 8 and
11) receive the broadcasted WSM message from the RSU and find out they may block the
30.
way of emergency vehicle (node 7), they will make the way for the emergency vehicle to
pass through. As such, the emergency vehicle can drive on a clear lane fast and safely.
(3) Dynamic Traffic Lights Control
The traffic lights are controlled by the traffic control center. The emergency vehicle
periodically broadcasts the WSM message which containing the request of traffic lights
control, its vehicle ID and location to the nearby RSU. The RSU will receive and relay this
message to the traffic control center. When the traffic control center receives the request of
traffic lights control, it will change the traffic lights on the intersection, which is in front of
the emergency vehicle, into green to pre-evacuate vehicles waiting for the traffic lights. By
doing so, we can avoid the emergency vehicle stuck in the traffic jam in front of the
intersection.
Fig. 4.2 A Simple Case of Dynamic Traffic Lights Control
31.
For instance, as one can see in Fig. 4.2, the emergency vehicle (node 7) periodically
broadcasts a WSM message which contains the request of traffic light control, vehicle ID,
and location. The nearby RSU (node 4) receives the WSM message and relays this message
to the traffic control center (node 5). Because the traffic light control center has the
shortest-time path information of the specified emergency vehicle ID, it changes the traffic
lights in front of the emergency vehicle into green. As such, vehicles (node 8, 9, 10, and 11)
can be pre-evacuated and will not make the emergency vehicle stuck in the traffic jam.
4.2. Design of the Scheme
The proposed traffic control mechanism is designed to reduce the arrival time of the
emergency vehicles to accident scenes. As described before, the traffic control mechanism
utilizes three major functions which are (1) moving path arrangement, (2) evacuation
message delivery, and (3) dynamic traffic lights control. We design various schemes to
evaluate how each scheme affects the arrival time of emergency vehicles to accident scenes.
As one can see in Table 4.1, we design four schemes to evaluate the arrival time of
emergency vehicles to accident scenes. These schemes are described below.
Scheme A: The proposed traffic control mechanism only applies the moving path
arrangement. The emergency vehicle will drive on the shortest-time path to the accident
scene. This scheme is the basic scheme used to compare with other schemes so that we can
evaluate the performance of each scheme.
Scheme B: The proposed traffic control mechanism applies both moving path
arrangement and evacuation message delivery. This scheme can help us analyze the effect of
the evacuation message delivery by comparing it to scheme A.
Scheme C: The proposed traffic control mechanism applies not only moving path
arrangement but also dynamic traffic lights control. By comparing to scheme A, we can
32.
evaluate the effect of the dynamic traffic lights control.
Scheme D: The proposed traffic control mechanism utilizes all three major functions
which are moving path arrangement, evacuation message delivery, and dynamic traffic
lights control. By comparing to scheme A, we can know the best performance improvement
of the proposed mechanism for emergency vehicles.
Table 4.1 Functions Used in Each Scheme
Scheme A Scheme B Scheme C Scheme D
Moving Path Arrangement ˇ ˇ ˇ ˇ
Evacuation Message Delivery ˇ ˇ
Dynamic Traffic Lights Control ˇ ˇ
4.3. Target Scenario
The target scenario simulated in this thesis is the road map near the Wan-Fang hospital
at Daan area in Taipei. Fig. 4.3 shows the road map near the Wan-Fang hospital captured
from the electronic roadmap system, UrMap [15]. We set the source S on the Wan-Fang
hospital and two accidents on position A and B. Therefore, there are two paths which are S
-> A and S -> B we will use in our simulation cases.
33.
Fig. 4.3 The Roadmap near Wan-Fang Hospital on UrMap
One can see the simulated road map on NCTUns in Fig. 4.4. With the help of NCTUns
network simulator, we can construct the road network by loading the real world road map
with shapefile format so that the moving paths of vehicles can be as real as possible. The
parameter settings of the target scenarios are described below.
34.
Fig. 4.4 The Roadmap near Wan-Fang Hospital on NCTUns
As one can see in Fig. 4.4, position S is the source location of the emergency vehicle at
Wan-Fang hospital, position A5 and B5 are the locations which are 25 intersections away
from the source S. One should know that the location A5/B5 is equal to the location A/B as
shown in Fig. 4.3. The parameters used in the simulated scenarios are shown in Table 4.2.
For each path, we set the destinations every 5, 10, 15, 20, and 25 intersections away from
the source S which are A1 to A5 and B1 to B5. We also apply various time periods of traffic
lights, which are 30, 60, 90 seconds, to analyze if time periods of traffic lights will affect the
performance of the proposed traffic control mechanism for each scenario. As shown in
Table 4.3, we evaluate two shortest time paths, which are path 1 and path 2, to see if driving
on different paths will significantly affect the performance of the proposed mechanism.
Table 4.4 shows the average vehicle separation distance for each scenario. We deploy
35.
vehicles on the road map using various vehicle separation distances which are 10, 20, and
30 (meter/vehicle/lane), respectively. This is equivalent to 30, 60, 90 road surface area per
vehicle when the road width is 3 meter. By doing so, we can analyze how average vehicle
separation distance affects the performance for each scenario.
Table 4.2 Parameter Settings of the Simulated Scenarios
Parameter Setting
Message Size (bytes) < 1,400
Network Protocol IEEE 802.11p/1609 WSMP
Source Wan-Fang Hospital
Simulation Time Source to destination
Network and Road Traffic Simulator NCTUns
Terrain Size (meter2) 2,000 * 1,500
Number of Vehicles 1,500 ~ 4,000
Road Width (meter) 3
Road Surface Area per Vehicle (meter2/vehicle) 30, 60, 90
Destination
(number of intersections away from the source) 5, 10, 15, 20, 25
Traffic Lights Period (second) 30, 60, 90
Table 4.3 Paths from Hospital to Accidents
Path Hospital to Accident
Path 1 S to A
Path 2 S to B
36.
Table 4.4 Average Vehicle Separation Distance
Traffic Condition
Average Vehicle Separation Distance
(meter/vehicle/lane)
A 10
B 20
C 30
37.
Chapter 5. Simulation Results
We use the arrival time reduction percentage (ATRP) based on scheme A to evaluate
the performance of a scheme under different traffic conditions, paths, and traffic lights
periods. The larger the ATRP, the better performance a scheme is. The definition of ATRP is
describe below.
Assume the arrival time of scheme A needs X seconds and the arrival time of an
evaluated scheme B, C, or D needs Y seconds, then the ATRP of the evaluated scheme is
calculated follows:
ATRP (%) = (X − Y)
X * 100 %
For conciseness, Table 5.1 shows the abbreviated terms that are used in the rest of this
thesis.
Table 5.1 Abbreviations
Term Abbreviation
Arrival Time Reduction Percentage ATRP
Traffic Lights Period TLP
Average Vehicle Separation Distance AVSD
As one can see in Fig. 5.1, the ATRP results under traffic condition A and when TLP is
30 seconds show that the performance of scheme A < that of scheme B < that of scheme C <
that of scheme D. The reasons are explained below.
On average, performances of scheme B, C, and D are better than scheme A. This is
because both evacuation message delivery and dynamic traffic lights control can greatly
help emergency vehicle drive fast and smoothly to the accident scene. The reason that
scheme C is better than scheme B is because the dynamic traffic lights control can prevent
38.
the emergency vehicle from being stuck in the traffic jam in front of the intersection. It also
shows the effect of dynamic traffic lights control is greater than that of evacuation message
delivery. Finally, the reason why scheme D has the best performance is because it not only
avoids the traffic obstruction in front of the traffic lights but also clears the way for the
emergency vehicle.
As shown in Fig. 5.1, in Fig. 5.2 and Fig. 5.3, one sees that when the AVSD increases,
the performance of each scheme decreases. This is because when AVSD becomes larger, the
emergency vehicle encounters less blocking of surrounding vehicles and therefore the
arrival time of the emergency vehicle to the accident scene becomes shorter in scheme A.
Compared with Fig. 5.4, in Fig. 5.5 and Fig. 5.6 one sees that the arrival time of scheme A
increases when AVSD decreases which proves the above description.
Fig. 5.1 The ATRP Results of Each Scheme on Path 1 under Traffic Condition A and when
TLP is 30 seconds
0
5
10
15
20
25
30
35
40
45
50
55
60
0 5 10 15 20 25 30
AT
RP
(%
)
Number of Traffic Lights
Scheme B
Scheme C
Scheme D
TLP = 30
AVSD = 10
PATH = 1
39.
Fig. 5.2 The ATRP Results of Each Scheme on Path 1 under Traffic Condition B and when
TLP is 30 seconds
Fig. 5.3 The ATRP Results of Each Scheme on Path 1 under Traffic Condition C and when
TLP is 30 seconds
0
5
10
15
20
25
30
35
40
45
50
55
60
0 5 10 15 20 25 30
AT
RP
(%
)
Number of Traffic Lights
Scheme B
Scheme C
Scheme D
TLP = 30
AVSD = 20
PATH = 1
0
5
10
15
20
25
30
35
40
45
50
55
60
0 5 10 15 20 25 30
AT
RP
(%
)
Number of Traffic Lights
Scheme B
Scheme C
Scheme D
TLP = 30
AVSD = 30
PATH = 1
40.
Fig. 5.4 The Arrival Time of Each Scheme on Path 1 under Traffic Condition A and when
TLP is 30 seconds
Fig. 5.5 The Arrival Time of Each Scheme on Path 1 under Traffic Condition B and when
TLP is 30 seconds
0
50
100
150
200
250
300
350
400
450
500
550
600
0 5 10 15 20 25 30
Arr
iva
l T
ime
(sec
on
ds)
Number of Traffic Lights
Scheme A
Scheme B
Scheme C
Scheme D
TLP = 30
AVSD = 10
PATH = 1
0
50
100
150
200
250
300
350
400
450
500
0 5 10 15 20 25 30
Arr
iva
l T
ime
(sec
on
ds)
Number of Traffic Lights
Scheme A
Scheme B
Scheme C
Scheme D
TLP = 30
AVSD = 20
PATH = 1
41.
Fig. 5.6 The Arrival Time of Each Scheme on Path 1 under Traffic Condition C and when
TLP is 30 seconds
Compared with Fig. 5.1, in Fig. 5.8, one sees that the performances of scheme B, C,
and D on path 2 are better than their performances on path 1 under traffic condition A and
when TLP is 30 seconds. This is because the total distance of path 2 is longer than that of
path 1 and therefore, in scheme A, emergency vehicle encounters more blockings caused by
surrounding vehicles and needs more time to arrive at the accident scene on path 2. Fig. 5.4
and Fig. 5.7 show the same results as described above. One can see that the arrival time of
scheme A in Fig. 5.7 is larger than in Fig. 5.4 but the arrival times of scheme B, C, and D in
Fig. 5.7 are just a little more than their arrival times in Fig. 5.4. Therefore, the performances
of scheme B, C, and D on path 2 are better than their performances on path 1 under traffic
condition A and when TLP is 30 seconds.
0
50
100
150
200
250
300
350
400
0 5 10 15 20 25 30
Arr
iva
l T
ime
(sec
on
ds)
Number of Traffic Lights
Scheme A
Scheme B
Scheme C
Scheme D
TLP = 30
AVSD = 30
PATH = 1
42.
Fig. 5.7 The Arrival Time of Each Scheme on Path 2 under Traffic Condition A and when
TLP is 30 seconds
Fig. 5.8 The ATRP Results of Each Scheme on Path 2 under Traffic Condition A and when
TLP is 30 seconds
When the TLP increases, the emergency vehicle can pass more traffic lights and also
move smoothly during the long green time in scheme A. However, the traffic lights periods
0
100
200
300
400
500
600
700
800
0 5 10 15 20 25 30
Arr
iva
l T
ime
(sec
on
ds)
Number of Traffic Lights
Scheme A
Scheme B
Scheme C
Scheme D
TLP = 30
AVSD = 10
PATH = 2
0
5
10
15
20
25
30
35
40
45
50
55
60
0 5 10 15 20 25 30
AT
RP
(%
)
Number of Traffic Lights
Scheme B
Scheme C
Scheme D
TLP = 30
AVSD = 10
PATH = 2
43.
will not significantly affect the arrival time of the emergency vehicle when the emergency
vehicle uses scheme D. This is because the emergency vehicle using scheme D has the
ability to control the traffic lights and empty a lane for itself. As shown in Fig. 5.9, one sees
that the arrival time of scheme A increases when TLP increases. One also sees that the
arrival time of scheme D is almost the same when TLP is variable in Fig. 5.10. Therefore, as
shown in Fig. 5.11, the ATRP performance of scheme D decreases when TLP increases.
Fig. 5.9 The Arrival Time of Scheme A on Path 2 under Traffic Condition A when TLP is
Variable
050
100150200250300350400450500550600650700750800
0 5 10 15 20 25 30
Arr
iva
l T
ime
(sec
on
ds)
Number of Traffic Lights
TLP 30
TLP 60
TLP 90
SCHEME = AAVSD = 10
PATH = 2
44.
Fig. 5.10 The Arrival Time of Scheme D on Path 2 under Traffic Condition A when TLP is
Variable
Fig. 5.11 The ATRP Results of Scheme D on Path 2 using Various TLPs under Traffic
Condition A
0
50
100
150
200
250
300
350
400
0 5 10 15 20 25 30
Arr
iva
l T
ime
(sec
on
ds)
Number of Traffic Lights
TLP 30
TLP 60
TLP 90
SCHEME = DAVSD = 10
PATH = 2
0
5
10
15
20
25
30
35
40
45
50
55
0 5 10 15 20 25 30
AT
RP
(%
)
Number of Traffic Lights
TLP 30
TLP 60
TLP 90
AVSD = 10
PATH = 2
45.
Chapter 6. Future Work
There are two enhancements that can be done in the future.
Use sensor-based locally controlled traffic lights switching
The traffic lights switching used in this thesis is globally synchronized. This
means that all the traffic lights statuses on the roadmap are changed in the same time.
We may develop a sensor-based locally controlled traffic lights switching which can
sense the traffic in the intersection so that the traffic lights can locally switch to
different signal status based on the different traffic condition in the intersection. We
can evaluate the effects of globally synchronized traffic lights switching and
sensor-based locally controlled traffic lights switching for our proposed traffic control
mechanism.
Assign the destination for every vehicle
In this thesis, surrounding vehicles use dynamic moving pattern to drive on the
road map. Although the vehicle has abilities to accelerate, decelerate, switch lane, and
detect the traffic lights, it doesn’t have any pre-assigned destination but just randomly
choose one direction at the intersection to move on. In the real world, every vehicle has
its destination to go. We could enhance the NCTUns network simulation to support the
assignment of destination for every vehicle so that the moving pattern of vehicles can
be as reasonable as possible.
46.
Chapter 7. Conclusion
In this thesis, a traffic control mechanism is proposed which utilizes three important
functions: (1) Moving path arrangement, (2) Evacuation message delivery, and (3) Dynamic
traffic lights control.
Our simulation results show that the proposed traffic control mechanism can
significantly reduce the arrival times of emergency vehicles to accident scenes in our
evaluated simulation cases. Our simulation results also show that the effect of dynamic
traffic lights control is larger than that of evacuation message delivery.
In our simulation, the proposed traffic control mechanism has better performance on a
dense vehicular network, i.e., when the average vehicle separation distance is small. This
is because the more vehicles on the roads, the more unexpected traffic blocking the
emergency vehicle may encounter. The proposed traffic control mechanism can eliminate
the unexpected traffic blocking and therefore an emergency vehicle can arrive at the
accident scene much fast and smoothly.
We found that using different traffic lights periods can affect the performance of the
proposed traffic control mechanism. Our results show that when the time period of traffic
lights increases in a dense vehicular network, the performance of the proposed traffic
control mechanism decreases. This is because when the green time increases, the traffic
condition on the roads becomes better. As a result, the advantage of the proposed traffic
control mechanism becomes less significant.
This thesis shows that our proposed traffic control mechanism can significantly reduce
30% to 50% arrival times required by emergency vehicles to arrive at accident scenes in our
evaluated cases. It is a feasible and very useful mechanism for life saving.
47.
Reference
[1] S.Y. Wang, C.L. Chou, C.H. Huang, C.C. Hwang, Z.M. Yang, C.C. Chiou, and C.C. Lin,
―The Design and Implementation of the NCTUns 1.0 Network Simulator,‖ Computer
Networks, Vol. 42, Issue 2, June 2003, pp. 175-197.
[2] The NCTUns 5.0, available at http://nsl10.csie.nctu.edu.tw/ .
[3] S.Y. Wang, C.L. Chou, Y.H. Chiu, Y.S. Tzeng, M.S. Hsu, Y.W. Cheng,W.L. Liu, and
T.W. Ho, ―NCTUns 4.0: An Integrated Simulation Platform for Vehicular Traffic,
Communication, and Network Researches,‖ 1st IEEE WiVec 2007 (International
Symposium on Wireless Vehicular Communications), Sep. 30, 2007, Baltimore, MD.
[4] ―IEEE 802.11p/D3.0,‖ IEEE Standards Activities Department. July 2007.
[5] ―IEEE Std 802.11-2007 (Revision of IEEE Std 802.11-1999,‖ June 12, 2007.
[6] ―IEEE 1609.1 Trial-Use Standard for Wireless Accesses in Vehicular Environments
(WAVE)—Resource Manager,‖ IEEE Vehicular Technology Society. October 2006.
[7] ―IEEE 1609.2 Trial-Use Standard for Wireless Accesses in Vehicular Environments
(WAVE)—Security Services for Applications and Management Messages,‖ IEEE
Vehicular Technology Society. October 2006.
[8] ―IEEE 1609.3 Trial-Use Standard for Wireless Accesses in Vehicular Environments
(WAVE)—Networking Services‖ IEEE Vehicular Technology Society. October 2006.
[9] ―IEEE 1609.4 Trial-Use Standard for Wireless Accesses in Vehicular Environments
(WAVE)—Multi-channel Operation‖ IEEE Vehicular Technology Society. October
2006.
[10] P. Hart, N. Nilsson, B. Raphael, ―A Formal Basis for the Heuristic Determination of
Minimum Cost Paths,‖ IEEE Transactions of Systems Science and Cybernetics, Vol.
48.
ssc-4, No. 2, July 1968.
[11] M. Miyawaki, Z. Yamashiro, T. Yoshida, ―Fast Emergency Preemption Systems
(FAST),‖ Intelligent Transportation Systems, 1999. Proceedings. 1999 IEEE/IEEJ/JSAI
International Conference on, 5-8 Oct. 1999 Page(s):993 – 997.
[12] C.M. Huang, C.C. Yang, C.Y. Tseng, C.H. Chou, ―A Centralized Traffic Control
Mechanism for Evacuation of Emergency Vehicles Using the DSRC Protocol,‖ Wireless
Pervasive Computing, 2009. ISWPC 2009. 4th International Symposium on, 11-13 Feb.
2009 Page(s):1 – 5.
[13] S.R. Rizvi, S. Olariu, M.C. Weigle, M.E. Rizvi, ―A Novel Approach to Reduce Traffic
Chaos in Emergency and Evacuation Scenarios,‖ Vehicular Technology Conference,
2007. VTC-2007 Fall. 2007 IEEE 66th
, Sept. 30 2007-Oct. 3 2007 Page(s):1937 – 1941.
[14] R.C. Vlad, C. Morel, J.Y. Morel, S. Vlad, ―A learning real-time routing system for
emergency vehicles,‖ Automation, Quality and Testing, Robotics, 2008. AQTR 2008.
IEEE International Conference on Volume 3, 22-25 May 2008 Page(s):390 – 395.
[15] UrMap Electronic Roadmap System, available at http://www.urmap.com/ .
[16] CAR 2 CAR Communication Consortium, ―CAR 2 CAR Communication Con-sortium
Manifesto, version 1.1,‖ Aug. 2007.